Explore the next evolution of Retrieval-Augmented Generation (RAG), where AI goes beyond text to integrate images, video, and audio. Multimodal RAG unlocks richer, more precise insights, but merging diverse data comes with challenges.

AI in logistics and supply chain: Optimizing processes and driving impact. Explore how AI optimizes demand forecasting, production planning, and inventory management, leading to more responsive and resilient supply chains.

Exploring bias in HR: Identifying sources of bias in AI-driven job-matching, tracking with fairness metrics, and leveraging architecture for transparency and mitigation.

Understand the essentials of AI literacy and its impact on your organization. Explore practical steps to build team-wide understanding, comply with regulations, and confidently navigate the complexities of AI integration.

This guide walks you through the process of building a powerful RAG pipeline using RAGLite. From configuring your LLM and database to implementing advanced retrieval strategies like semantic chunking and reranking, this guide covers everything you need to optimize and scale your RAG-based applications.

Discover RAGLite, a lightweight toolkit that revolutionizes Retrieval-Augmented Generation (RAG). With features like semantic chunking, adaptive retrieval, and hybrid search, RAGLite overcomes traditional RAG limitations, simplifying workflows and ensuring fast, scalable, and accurate information retrieval for real-world AI applications.

Unsupervised anomaly detection advances quality control in manufacturing by enabling efficient and flexible product defect detection with a minimal labelling effort and the ability to handle changing products and various defect types.

Imagine an AI that can navigate your computer like a human, clicking buttons, typing commands, and seamlessly interacting with digital interfaces. Explore Anthropic's groundbreaking advancements in Claude AI.

VTM's The Masked Singer has brought back ONTMASKATRON 2.0, an AI-powered detective created by Superlinear, to help unmask celebrities.

What hidden insights are buried in your unstructured data? Discover how Generative AI can unlock valuable business intelligence, turning data challenges into growth opportunities.

MLOps streamlines AI operations, ensuring scalable, reliable, and efficient model performance.

Get exclusive insights, practical applications, early access to events, and join a thriving community of AI professionals.

The scale and complexity companies have to contend with is continually increasing (McKinsey & Company, 2020). To keep up with this, data-driven forecasting has become crucial for making informed business decisions.

Who is better suited to talk about what it’s like working at Superlinear, an AI consulting company in Brussels, than someone who actually works at Superlinear? In this blog post, we let Joseph, Team Lead and Solution Architect, do the talking.

Dreaming of a career in AI? Master these 10 essential skills to become a successful AI Engineer, from coding to problem-solving and beyond.

Football is not just a game; it’s a global phenomenon that unites fans across continents. The passion, the excitement, and the drama of certain match sequences captivate millions of fans across the globe.

Foundation models hold promise for time series forecasting but remain underdeveloped. Superlinear, AI consultancy, tests three models—TimeGPT, Lag-Llama, and Chronos—revealing mixed results, with traditional methods still outperforming them in many scenarios.

Learn how to implement efficient operations research (OR) solutions using OR-Tools. This guide offers practical tips, covering key strategies like optimizing variables and constraints, trying different solvers, and adding symmetry-breaking constraints.

Discover how to assess LLM-based applications by building robust test sets, handling diverse valid outputs, and overcoming evaluation challenges.

Learn how to efficiently forecast timestamped tabular data by combining time series and tabular models. This approach is useful for applications like demand forecasting and predictive maintenance.

The internet has been overflooded by stunning visuals created by Generative AI. And it seems all you need to do is “talk” to the AI? Let’s start with the elephant in the room: Will AI replace the creator or designer?

Superlinear’s Poetry Cookiecutter simplifies GPU setup for machine learning projects while boosting reproducibility. Developers can run code on CPUs or GPUs without modification.

AI-generated images have been used for everything from winning art competitions to protecting the identity of anti-government protesters, but are they usable in a business context? What about the controversy about these models from artists and other content creators?

Boost crop classification accuracy by applying techniques like data augmentation, noise reduction, and model calibration for refined remote sensing results.

Today’s world is highly unpredictable. Global events (COVID-19 pandemic, the blockage of the Suez channel and the geopolitical situation, etc. ) as well as local scale events such as variable customer demand, supplier delay and equipment failure make it increasingly difficult for companies to manage their value chain efficiently. 

The AI landscape is changing fast. Foundation models have taken a huge leap forward, leading to more cost-effective AI solutions while unlocking increasingly more value in practically every business process. This has created a new reality in the AI landscape, with sometimes more questions than answers.

This article aims to decode four main MLOps components. MLOps is an extensive field that includes numerous elements. In this piece, Shoera Sels provides you with the MLOps structure, helping you understand what it encompasses

Join us in this two-part blog series as we, Ruben Broekx and Mattia Molon, Machine Learning Engineer at Superlinear, collaborate with domain experts from VITO Remote Sensing to create a pixel-based crop classification model.

How can we use Artificial Intelligence to create a more sustainable future? At a recent AI Café organized by Superlinear, a group of AI experts convened to discuss the potential of AI in fighting climate change.

How can Artificial Intelligence contribute to a more sustainable future? In a recent AI Café hosted by Superlinear, a panel of five AI experts gathered to explore the role of AI in addressing sustainability challenges.

How can Artificial Intelligence contribute to a more sustainable future? In a recent AI Café hosted by Superlinear, a panel of five AI experts gathered to explore the role of AI in combating climate change.

How can we use Artificial Intelligence to create a more sustainable future? At a recent AI Café organized by Superlinear, five AI experts convened to discuss the potential of AI in fighting climate change.

Curious about how to elevate your organization’s AI capabilities? In this second post of our MLOps series, we walk you through the steps to assess your current MLOps maturity and kick-start your journey towards a robust AI strategy.

Curious about the buzz around MLOps and how it can boost your organization’s AI capabilities? In this first post of a three-part series, Shoera Sels unpacks the core benefits of MLOps (Machine Learning Operations) and why it’s essential for harnessing AI's full potential.

How can we use artificial Intelligence to create a more sustainable future? At a recent AI Café organized by Superlinear, five AI experts convened to discuss the potential of AI in fighting climate change.

Large Language Models (LLMs) like ChatGPT are making waves for their potential while sparking debates on ethics and regulation. Some see GPT-4 as a step toward Artificial General Intelligence, but concerns about privacy, data security, and compliance remain pressing.

This post outlines the current state of GPTs and provides predictions for the next 6, 12, and 24 months concerning their evolution in six key dimensions. The analysis offers valuable insights into the advancements and potential challenges we can expect in the near future.

GPT-4 has taken the world by storm, impressing everyone with its capability to solve a wide range of tasks. Microsoft researchers recently released a paper [1] where they claim to have observed the first ‘sparks’ of artificial general intelligence in GPT-4. 

While supporting other companies in their AI journey, I have had the unique opportunity to witness the fascinating evolution of GPTs, transforming from information-gathering tools to powerful, action-oriented assistants.

Explore the rapid evolution of AI and GPT-4's transformative power. Learn how organizations can develop a roadmap to adopt AI innovations and maintain a competitive edge in the next 3, 6, 12, and 24 months.

Discover five key strategies to unlock the true potential of AI within your organization. Learn from real-world examples, like Brussels Airport, on how AI can drive growth and operational improvements

Learn how Chat GPT-4 can be tailored to your data and help increase efficiency in your business. Get insights on incorporating GPT-4 to solve complex tasks and leverage its capabilities for innovative solutions.

Despite challenges in emotion recognition software, this post explores its practical use cases and how businesses can address the ethical and technical issues to unlock value from Emotional AI systems.

Dive into the technical details of continuously retraining a recommender system with MLOps. Learn how MLOps can improve the effectiveness of ML projects and ensure continuous optimization for ML Engineers.

Explore how to implement live predictions for key business metrics using MLOps. This in-depth post offers technical insights for Machine Learning Engineers on building effective MLOps Stacks for real-time applications.

Learn how to serve and scale multiple computer vision models for mobile apps with MLOps. This guide provides detailed technical insights for ML Engineers on how to build robust MLOps frameworks.

Understand the key principles shared between MLOps vs DevOps. This post explains how to apply DevOps best practices to MLOps for smoother AI integration and quicker model deployment.

Learn why AI projects often fail and how to solve these issues. Our CEO shares valuable insights on how to integrate AI successfully within organizations, based on years of experience across industries.

Curious about what it’s like to be a Machine Learning intern at Superlinear? Discover firsthand experiences from our intern Martijn Leplae, including the challenges, growth opportunities, and team environment.

Learn how CERM tackled the challenges of the printing industry with the help of AI specialist Superlinear. Explore how innovative AI-driven solutions can optimize scheduling, reduce production times, and improve flexibility.

Discover how Superlinear’s AI Solution Leads drive meaningful impact for mission-driven organizations. Learn about their role in using AI as a catalyst for global progress in health, safety, and sustainability.

Involving end users early in AI projects is critical to success. Explore real-world examples, including how Superlinear collaborated with a specialized lab to create AI-driven solutions that boosted efficiency.

Find out how AI can significantly improve key customer success metrics. This post highlights four crucial KPIs and explains how AI-driven strategies can drive customer satisfaction and business growth.

Learn how multichannel image detection using infrared (IR) spectrum enhances night-time autonomous driving. This post explains how Superlinear modified YOLOv5 to improve real-time object detection models.

Discover the risks of skipping MLOps in AI projects. Superlinear’s Senior ML Engineer Stijn Goossens shares firsthand insights on why MLOps is essential for deploying efficient and scalable AI solutions.

Starting your MLOps journey? This guide covers four essential steps to streamline AI project development, control complexity, and improve deployment speed as your AI initiatives scale.

Learn how the upcoming Digital Services Act (DSA) impacts AI-driven services. This blog breaks down key considerations for CIOs, including transparency requirements and the future of algorithmic responsibility.

Join a thought-provoking conversation between Superlinear CEO Davio Larnout and Google UX Manager Josh Lovejoy on why purpose, fairness, and CSR are vital for shaping the future of AI development.

Thinking of a career move? Hear from senior ML engineers at Superlinear about their top reasons for joining a fast-growing AI scale-up, including growth opportunities, team dynamics, and long-term potential.

Uncover the truth behind common AI myths that may be holding your business back. With insights from AI expert Seppe vanden Broucke, we debunk misconceptions that stop companies from embracing AI.

Learn how Azure Batch can handle large-scale parallel workloads efficiently. This guide offers a quick look at how Superlinear used Azure Batch to balance scalability, time, and cost in backend calculations.

Discover how AI can transform customer success teams, reducing repetitive tasks and enabling them to focus on building strong customer relationships and maximizing lifetime value.

Learn how AI helps quality control teams detect issues faster and more accurately across industries like food, medicine, and manufacturing, reducing costs and improving efficiency.

Is AI too focused on accuracy? Explore why companies should think beyond accuracy when developing AI solutions and how this shift can unlock greater business value.

Explore how AI could enhance performance in professional cycling, with a focus on improving strategy and decision-making for top athletes like Wout Van Aert in major races.

Learn five key strategies to unlock AI’s potential and create meaningful impact for your business, from identifying key struggles to implementing practical AI-driven solutions.

Discover how AI can close knowledge gaps within your organization, increasing team efficiency, boosting employee confidence, and prioritizing AI solutions that deliver the most impact.

Stay ahead of the game with a breakdown of the EU AI Act, a proposed regulation that will impact businesses using AI in Europe. Learn what to keep in mind as you develop AI solutions.

Unlock the potential of unstructured data with keyword extraction in Natural Language Processing (NLP). Learn how this technique can transform your business intelligence and analytics.

Think machine learning always requires vast amounts of data? Think again. Explore how ML can be done with minimal or no data, and what this means for your business and AI projects.

Learn how adopting a data-centric approach to machine learning can maximize the effectiveness of your models, focusing on data quality and its impact on AI system performance.

Discover why MLOps is essential for developing and maintaining production ML systems, and learn how you can adopt MLOps to streamline your machine learning projects.

Get ready for your dream job at Superlinear! Our HR manager shares valuable tips and tricks to help you ace your interview and prepare to become a Machine Learning Engineer.

Explore how AI can optimize supply chain operations, from demand forecasting to route optimization. Learn how Superlinear approaches supply chain AI projects for maximum efficiency.

Starting a new job remotely? Hear from Superlinear employees about their experiences onboarding and working from home, and how remote work has impacted efficiency and team spirit.

Learn how computer vision is revolutionizing agriculture. This blog walks through the process of field boundary detection using satellite imagery, a key tool in sustainable farming.

Looking to start your AI journey as a student? Here are three actionable tips to help you gain AI skills, from joining a community to pursuing education and internships.

Learn the key skills your team needs to apply AI in practice. Explore different roles in AI projects and discover how to tailor training for success.

Continue your journey into document embeddings with this in-depth guide. In Part 2, we introduce evaluation metrics and test different embedding approaches, while also exploring advanced techniques for improved results.

Discover nine reasons why Superlinear is the perfect workplace for AI enthusiasts. Join us to empower people with AI, grow your skills, and make a real impact.

Discover how to design AI-driven user experiences that foster trust and collaboration. Learn strategies to enhance user-AI interaction and prevent errors.

Learn how to build document embeddings through real-world examples. Discover how we improved VDAB's career orientation test using a data-driven approach to match jobseekers with professions.

Learn how to overcome the challenges of moving AI projects from PoC to production. Download our guide for expert insights and solutions.

Explore how AI is transforming manufacturing by boosting efficiency and supporting operators, while helping companies stay competitive and grow.

Discover how to leverage Machine Learning to identify the issue of low-contrast text on a web page.

COVID-19 accelerated AI adoption in the public sector, helping governments digitize services, manage remote work, and improve citizen engagement.

AI enhances productivity by automating repetitive tasks, enabling employees to focus on creative work. This human-centered approach boosts efficiency.

Graph machine learning uses graph neural networks to analyze complex relationships in data. It is applied in recommender systems, anomaly detection, and biology.

Superlinear’s AI solution helps Flemish exporters by speeding up responses to inquiries. AI-powered tools improve efficiency by 36% and response times by 27%.

Use FastAPI, Docker, and Terraform to swiftly write, deploy, and scale APIs, staying agile in machine learning app development.

EU companies face challenges using US cloud services post-Schrems II due to GDPR concerns. Mitigations include encryption and European providers.

AI enhances patient engagement through tools like sentiment analysis, remote monitoring, appointment reminders, and simplified medical information.

AI in media enhances fact-checking, trend detection, video tagging, content summaries, and personalized recommendations, boosting user engagement.

Martin’s internship at Superlinear involved improving TalentAPI, working remotely, and gaining hands-on experience in machine learning and backend development.

To effectively communicate AI results, focus on simplifying explanations, use examples, and ensure transparency. Explain model decisions clearly for better client understanding.

AIOps automates DevOps for AI projects, reducing manual effort and boosting efficiency. It’s a growing trend, helping companies lower costs.

Boost team spirit remotely with activities like Donut calls, Watch & Learn sessions, happy hours, business updates, and knowledge sharing.

To make your AI project GDPR-compliant, focus on principles like data minimization, fairness, transparency, and accuracy, ensuring ethical AI use.

VDAB and Superlinear use AI to predict jobs that match jobseekers’ interests. AI shortens the orientation test from 45 to 10 minutes.

Five keys to AI project success: define clear objectives, ensure data quality, involve stakeholders, iterate quickly, and focus on long-term value.

To make AI projects GDPR-compliant, follow 7 principles: lawfulness, data minimization, accuracy, storage limits, and security. Balance privacy with efficiency.

AI in design allows human creativity to focus on meaning, while AI handles details, scaling, and personalization efficiently.

Erasmus inspired Superlinear women to pursue AI careers by building skills like determination, creativity, and language, despite varied backgrounds.

C-level executives can promote fairness in AI by making difficult decisions, balancing accuracy with fairness, and addressing biases proactively.

Superlinear’s #LeerInUwKot app helps users find online courses during lockdown. It uses AI to match skills with relevant learning opportunities.

Life sciences firms can adopt AI by focusing on impactful areas, iterating solutions, and enhancing processes like drug research and automation.

Tips to enhance communication skills while working from home, focusing on clarity and conciseness.

Serverless platforms can support AI but face limitations in execution times, storage, and scaling.

A solution to improve Belgian NLP by handling regional language complexities with an accessible framework.

For all the buzz surrounding the introduction of GPT-3, a sober look at the new AI model shows that it’s not a quantum leap in artificial intelligence. For some specific applications, it can be very useful. But for broader use in the real world, GPT-3 falls short, as it still delivers the equivalent of pink slime rather than nutritious meat.

AI can optimize HR processes like recruitment and employee management, improving efficiency and decision-making.

A guide to using Python’s Aiohttp library for building performant, asynchronous HTTP applications.

JavaScript use in SPAs is vulnerable to XSS and CSRF attacks, requiring strategies to secure API tokens.

Key lessons for building a data science team: balance, feedback, start small, use existing data, and ensure management buy-in.

Use Amazon SageMaker with TensorFlow to build, train, and deploy a CNN model for fashion item classification.

Set up an AWS EC2 instance with GPU support for TensorFlow using Docker to efficiently run deep learning tasks.